Feature Selection and Categorization to Design Reliable Fault Detection Systems
H. Senoussi,
B. Chebel-Morello,
M. Denaï
et al.
Abstract:In this work, we will develop a fault detection system which is identified as a classification task. The classes are the nominal or malfunctioning state. To develop a decision system it is important to select among the data collected by the supervision system, only those carrying relevant information related to the decision task. There are two objectives presented in this paper, the first one is to use data mining techniques to improve fault detection tasks. For this purpose, feature selection algorithms are a… Show more
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